More than a million women have left the labor market. The Fed must take them into account because it defines “full employment”
Mission accomplished in monetary policy is a moving target. The Fed’s mandate to maximize employment and price stability exists in a dynamic economic system with diverse economic actors. While we shouldn’t expect policy makers to hit the bull’s eye, we should expect them to use the most accurate and effective tools available.
In the case of maximum employment, the Fed aims to achieve the highest level of employment without driving up inflation. The sweet spot for maximum employment is between 4.1% and 4.7% unemployment rate. Some types of unemployment, such as frictional or transitory cyclical unemployment, support our economy by stabilizing wages and therefore mitigating inflation, hence why an unemployment rate closer to 0 is never the objective.
July’s headline unemployment rate came in at 3.5%, well below the maximum recommended employment range. This level of unemployment screams “too hot – take action”. And indeed, the Fed has heard the call. Already this year, they set the fastest pace of interest rate hikes in four decades to calm the economy. The Federal Free Market Rates Meeting in September will continue the trend. However, the meaning of the call changes if we look at the disaggregated data.
The madness of ignorant gender indicators
When we deal with the percentages that control population growth, the female labor force participation rate was 59.2% on the eve of the pandemic. As of September 2, 2022, it was 58.4%. This means that the US labor force has lost 1.067 million women since February 2020. If we include these missing women in the August unemployment figures, the female unemployment rate would be 4.6%, or at the upper limit. maximum employment.
It’s all women. For black women, counting the 309,000 absent from the labor market since the start of the pandemic, their unemployment rate is 8.5%. For Latinos, counting the 252,000 of them absent from the labor force since the start of the pandemic, their unemployment rate is 6.1%. Maybe economists shouldn’t have been so quick to announce the all-time low unemployment rate of 3.7% for Latinas last month.
Disaggregated economic indicators do not say “calm down”. In some cases they say “warm up”. So how should we act on these seemingly contradictory signals without unleashing excessive chaos?
A fair solution
Disaggregated data is important because it sharpens our view of the economy. A finer view of the economy is important because it optimizes decision-making. For example, if we brought back the 1.067 million women absent from the labor force since February 2020, we could close the gap between workers and open jobs by almost 25%.
This, in turn, would prevent the economy from overheating by reducing the demand for workers. Right now, our economy has nearly two open jobs for every job seeker, and employers need to raise wages to attract and retain workers. Identify the wage-price spiral.
Instead of raising interest rates to cool the economy (an inequitable “solution” that hurts women and people of color the most), data disaggregated by gender and race suggests a different, more equitable solution: we should increase labor supply by returning 1.067 million missing women to the workforce. This would stabilize prices, ensure a more inclusive recovery and revive equitable economic growth.
We are all paying the price for gender-blind policy-making. Women have added $2 trillion to the US economy since 1970 by increasing their participation in the workforce. The pandemic has siphoned off 63% of that progress, or $1.26 trillion in economic potential.
Not creating policies to bring women back into the workforce is a breach of fiduciary responsibility, as it keeps the $3.1 trillion potential of gender equity trapped in the cracks of our economy. It also means the Fed is not living up to its congressional mandate to “aim for maximum employment and price stability.”
We can overcome gender ignorance by applying the intersectional lens of gender to economic data. Then we can use this more accurate view of the economy to inform more efficient, effective and equitable policies.
Katica Roy is the CEO of Pipeline.
The opinions expressed in Fortune.com comments are solely the opinions of their authors and do not reflect the opinions and beliefs of Fortune.
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